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Abstract Ocean spring phytoplankton blooms are dynamic periods important to global primary production. We document vertical patterns of a diverse suite of eukaryotic algae, the prasinophytes, in the North Atlantic Subtropical Gyre with monthly sampling over four years at the Bermuda Atlantic Time-series Study site. Water column structure was used to delineate seasonal stability periods more ecologically relevant than seasons defined by calendar dates. During winter mixing, tiny prasinophytes dominated by Class II comprise 46 ± 24% of eukaryotic algal (plastid-derived) 16S rRNA V1-V2 amplicons, specifically Ostreococcus Clade OII, Micromonas commoda, and Bathycoccus calidus. In contrast, Class VII are rare and Classes I and VI peak during warm stratified periods when surface eukaryotic phytoplankton abundances are low. Seasonality underpins a reservoir of genetic diversity from multiple prasinophyte classes during warm periods that harbor ephemeral taxa. Persistent Class II sub-species dominating the winter/spring bloom period retreat to the deep chlorophyll maximum in summer, poised to seed the mixed layer upon winter convection, exposing a mechanism for initiating high abundances at bloom onset. Comparisons to tropical oceans reveal broad distributions of the dominant sub-species herein. This unparalleled window into temporal and spatial niche partitioning of picoeukaryotic primary producers demonstrates how key prasinophytes prevail in warm oceans.

Abstract The concentration of chlorophyll‐a (CHL) is an important proxy for autotrophic biomass and primary production in the ocean. Quantifying trends and variability in CHL are essential to understanding how marine ecosystems are affected by climate change. Previous analyses have focused on assessing trends in CHL mean, but little is known about observed changes in CHL extremes and variance. Here we apply a quantile regression model to detect trends in CHL distribution over the period of 1997–2022 for several quantiles. We find that the magnitude of trends in upper quantiles of global CHL (>90th) are larger than those in lower quantiles (≤50th) and in the mean, suggesting a growing asymmetry in CHL distribution. On a regional scale, trends in different quantiles are statistically significant at high latitude, equatorial, and oligotrophic regions. Assessing changes in CHL distribution has potential to yield a more comprehensive understanding of climate change impacts on CHL.

The launch of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) and the Surface Biology and Geology (SBG) satellite sensors will provide increased spectral resolution compared to existing platforms. These new sensors will require robust calibration and validation datasets, but existing field-based instrumentation is limited in its availability and potential for geographic coverage, particularly for coastal and inland waters, where optical complexity is substantially greater than in the open ocean. The minimum signal-to-noise ratio (SNR) is an important metric for assessing the reliability of derived biogeochemical products and their subsequent use as proxies, such as for biomass, in aquatic systems. The SNR can provide insight into whether legacy sensors can be used for algorithm development as well as calibration and validation activities for next-generation platforms. We extend our previous evaluation of SNR and associated uncertainties for representative coastal and inland targets to include the imaging sensors PRISM and AVIRIS-NG, the airborne-deployed C-AIR radiometers, and the shipboard HydroRad and HyperSAS radiometers, which were not included in the original analysis. Nearly all the assessed hyperspectral sensors fail to meet proposed criteria for SNR or uncertainty in remote sensing reflectance (Rrs) for some part of the spectrum, with the most common failures (>20% uncertainty) below 400 nm, but all the sensors were below the proposed 17.5% uncertainty for derived chlorophyll-a. Instrument suites for both in-water and airborne platforms that are capable of exceeding all the proposed thresholds for SNR and Rrs uncertainty are commercially available. Thus, there is a straightforward path to obtaining calibration and validation data for current and next-generation sensors, but the availability of suitable high spectral resolution sensors is limited.

A massive bloom of the raphidophyte Heterosigma akashiwo occurred in summer 2022 in San Francisco Bay, causing widespread ecological impacts including events of low dissolved oxygen and mass fish kills. The rapidly evolving bloom required equally rapid management response, leading to the use of near-real-time image analysis of chlorophyll from the Ocean and Land Colour Instrument (OLCI) aboard Sentinel-3. Standard algorithms failed to adequately capture the bloom, signifying a need to refine a two-band algorithm developed for coastal and inland waters that relates the red-edge part of the remote sensing reflectance spectrum to chlorophyll. While the bloom was the initial motivation for optimizing this algorithm, an extensive dataset of in-water validation measurements from both bloom and non-bloom periods was used to evaluate performance over a range of concentrations and community composition. The modified red-edge algorithm with a simplified atmospheric correction scheme outperformed existing standard products across diverse conditions, and given the modest computational requirements, was found suitable for operational use and near-real-time product generation. The final version of the algorithm successfully minimizes error for non-bloom periods when chlorophyll a is typically −3, while also capturing bloom periods of >100 mg m−3 chlorophyll a.

Kelp forests dominate autotrophic biomass and primary productivity of approximately 30,000 to 60,000 km of shallow temperate and Arctic rocky reef coastline globally and contribute significantly to carbon cycling in the coastal ocean. Rapid biomass turnover is driven by very high growth rates and seasonal environmental drivers. As a result, kelp biomass varies greatly with time, space, and by species. In the northeast Pacific region, bull kelp (Nereocystis leutkeana) and giant kelp (Macrocystis pyrifera) form extensive floating surface canopies with a distinct spectral signature compared to the surrounding water. Studies have shown that remote sensing is advantageous for deriving large-scale estimates of floating surface canopy biomass, which comprises more than 90% of bull and giant kelp standing stock. However, development and validation of remotely derived kelp canopy biomass is lacking because existing approaches are time intensive and costly. This study attempted to close that gap by developing a rapid survey design utilizing diver and unmanned aerial vehicle (UAV) imagery across six sites in northern and central California. Kelp sporophytes were collected and measured for morphometric characteristics and genera-specific allometry to canopy biomass. Kelp density was measured using in situ diver surveys and coupled with UAV imagery to quantify kelp canopy biomass at a range of ground sampling distances. We successfully estimated kelp canopy biomass from UAV imagery at 33% (2/6) of the survey sites, but consistently determining canopy biomass via this approach was challenged by both survey design and kelp patch-specific spatial characteristics. The morphologies of bull kelp in Monterey were significantly different than other regions measured, but further work should be conducted to fully characterize differences in canopy biomass at the regional and sub-regional scale. We use this opportunity to suggest survey design strategies that will increase the success of future methodological development of UAV biomass retrieval. We also recommend developing long-term, annual genera-specific monitoring programs across the northeast Pacific region and beyond to validate remote sensing derived biomass estimates beyond the small number of existing well-characterized sites.

Meredith McPherson et al. use a 34-year time series of satellite and in situ derived data to study bull kelp forests of northern California and demonstrate the ecosystem shifts following a marine heatwave event between 2014 and 2016. The results show that increased herbivory by sea urchins due to the loss of a predator reduced bull kelp forest resistance to fluctuating environmental conditions and point to the importance of ecosystem-based and adaptive management strategies.

Offshore aquaculture has the potential to expand the macroalgal industry. However, moving into deeper waters requires suspended structures that will present novel farm-environment interactions. Here, we present a computational modeling framework, the Macroalgal Cultivation Modeling System (MACMODS), to explore within-farm modifications to light, seawater flow, and nutrient fields across time and space scales relevant to macroalgae. A regional ocean model informs the site-specific setting, the Santa Barbara Channel in the Southern California Bight. A fine-scale hydrodynamic model predicts modified flows and turbulent mixing within the farm. A spatially resolved macroalgal growth model, parameterized for giant kelp, Macrocystis pyrifera, predicts kelp biomass. Key findings from model integration are that regional ocean conditions set overall farm performance, while fine-scale within-farm circulation and nutrient delivery are important to resolve variation in within-farm macroalgal performance. Therefore, we conclude that models resolving within-farm dynamics can provide benefit to farmers with insight on how farm design and regional ocean conditions interact to influence overall yield. Here, the presence of repeating longlines aligned with the mean current generate flow diversions around the farm as well as attached Langmuir circulations and increased turbulence intensity. These flow-induced phenomena lead to less biomass in the interior portion of the farm relative to the edges. We also find that there is an effluent “footprint” that extends as much as 20 km beyond the farm. In this regard, MACMODS can be used to not only evaluate farm design and cultivation practices that maximize yield but also explore interactions between the farm and ecosystem in order to minimize impacts.

Maintaining healthy, productive ecosystems in the face of pervasive and accelerating human impacts including climate change requires globally coordinated and sustained observations of marine biodiversity. Global coordination is predicated on an understanding of the scope and capacity of existing monitoring programs, and the extent to which they use standardized, interoperable practices for data management. Global coordination also requires identification of gaps in spatial and ecosystem coverage, and how these gaps correspond to management priorities and information needs. We undertook such an assessment by conducting an audit and gap analysis from global databases and structured surveys of experts. Of 371 survey respondents, 203 active, long-term (>5 years) observing programs systematically sampled marine life. These programs spanned about 7% of the ocean surface area, mostly concentrated in coastal regions of the United States, Canada, Europe, and Australia. Seagrasses, mangroves, hard corals, and macroalgae were sampled in 6% of the entire global coastal zone. Two-thirds of all observing programs offered accessible data, but methods and conditions for access were highly variable. Our assessment indicates that the global observing system is largely uncoordinated which results in a failure to deliver critical information required for informed decision-making such as, status and trends, for the conservation and sustainability of marine ecosystems and provision of ecosystem services. Based on our study, we suggest four key steps that can increase the sustainability, connectivity and spatial coverage of biological Essential Ocean Variables in the global ocean: (1) sustaining existing observing programs and encouraging coordination among these; (2) continuing to strive for data strategies that follow FAIR principles (findable, accessible, interoperable, and reusable); (3) utilizing existing ocean observing platforms and enhancing support to expand observing along coasts of developing countries, in deep ocean basins, and near the poles; and (4) targeting capacity building efforts. Following these suggestions could help create a coordinated marine biodiversity observing system enabling ecological forecasting and better planning for a sustainable use of ocean resources.

The marine biotoxin domoic acid (DA) is an analog of the neurotransmitter glutamate that exerts potent excitatory activity in the brain, heart, and other tissues. Produced by the diatom Pseudo-nitzschia spp., DA accumulates in marine invertebrates, fish, and sediment. Southern sea otters (Enhydra lutris nereis) feed primarily on invertebrates, including crabs and bivalves, that concentrate and slowly depurate DA. Due to their high prey consumption (25% of body weight/day), sea otters are commonly exposed to DA. A total of 823 necropsied southern sea otters were examined to complete this study; first we assessed 560 subadult, adult, and aged adult southern sea otters sampled from 1998 through 2012 for DA-associated pathology, focusing mainly on the central nervous system (CNS) and cardiovascular system. We applied what was learned to an additional cohort of necropsied sea otters of all demographics (including fetuses, pups, juveniles, and otters examined after 2012: n = 263 additional animals). Key findings derived from our initial efforts were consistently observed in this more demographically diverse cohort. Finally, we assessed the chronicity of DA-associated pathology in the CNS and heart independently for 54 adult and aged adult sea otters. Our goals were to compare the temporal consistency of DA-associated CNS and cardiovascular lesions and determine whether multiple episodes of DA toxicosis could be detected on histopathology. Sea otters with acute, fatal DA toxicosis typically presented with neurological signs and severe, diffuse congestion and multifocal microscopic hemorrhages (microhemorrhages) in the brain, spinal cord, cardiovascular system, and eyes. The congestion and microhemorrhages were associated with detection of high concentrations of DA in postmortem urine or gastrointestinal content and preceded histological detection of cellular necrosis or apoptosis. Cases of chronic DA toxicosis often presented with cardiovascular pathology that was more severe than the CNS pathology; however, the lesions at both sites were relatively quiescent, reflecting previous damage. Sea otters with fatal subacute DA toxicosis exhibited concurrent CNS and cardiovascular pathology that was characterized by progressive lesion expansion and host response to DA-associated tissue damage. Acute, subacute, and chronic cases had the same lesion distribution in the CNS and heart. CNS pathology was common in the hippocampus, olfactory, entorhinal and parahippocampal cortex, periventricular neuropil, and ventricles. The circumventricular organs were identified as important DA targets; microscopic examination of the pituitary gland, area postrema, other circumventricular organs, and both eyes facilitated confirmation of acute DA toxicosis in sea otters. DA-associated histopathology was also common in cardiomyocytes and coronary arterioles, especially in the left ventricular free wall, papillary muscles, cardiac apex, and atrial free walls. Progressive cardiomyocyte loss and arteriosclerosis occurred in the same areas, suggesting a common underlying mechanism. The temporal stage of DA-associated CNS pathology matched the DA-associated cardiac pathology in 87% (n = 47/54) of cases assessed for chronicity, suggesting that the same underlying process (e.g., DA toxicosis) was the cause of these lesions. This temporally matched pattern is also indicative of a single episode of DA toxicosis. The other 13% of examined otters (n = 7/54) exhibited overlapping acute, subacute, or chronic DA pathology in the CNS and heart, suggestive of recurrent DA toxicosis. This is the first rigorous case definition to facilitate diagnosis of DA toxicosis in sea otters. Diagnosing this common but often occult condition is important for improving clinical care and assessing population-level impacts of DA exposure in this federally listed threatened subspecies. Because the most likely source of toxin is through prey consumption, and because humans, sea otters, and other animals consume the same marine foods, our efforts to characterize health effects of DA exposure in southern sea otters can provide strong collateral benefits.

A heatwave that blanketed the northeast Pacific Ocean in 2013–2015 had severe impacts on the marine ecosystem through altered species composition and survival. A direct result of this marine heatwave was a sustained, record-setting harmful algal bloom (HAB), caused by the toxigenic diatom, Pseudo-nitzschia, that led to an unprecedented delay in harvest opportunity for commercial Dungeness crab (Metacarcinus magister) and closure of other recreational, commercial and tribal shellfish harvest, including razor clams. Samples collected during a cruise in summer 2015, showed the appearance of a highly toxic “hotspot” between Cape Mendocino, CA and Cape Blanco, OR that was observed again during cruises in the summers of 2016–2018. The transport of toxic cells from this retentive site northward during wind relaxations or reversals associated with storms resulted in economically debilitating delay or closure of Dungeness crab harvest in both northern California and Oregon in 2015–2019. Analyses of historic large-scale Pseudo-nitzschia HABs have shown that these events occur during warm periods such as El Niño, positive phases of the Pacific Decadal Oscillation, or the record-setting marine heatwave. In order to reduce the impacts of large-scale HABs along the west coast of North America, early warning systems have been developed to forewarn coastal managers. These early warning systems include the Pacific Northwest and California HAB Bulletins, both of which have documented elevated domoic acid and increased risk associated with the northern California hotspot. These early warnings enable mitigative actions such as selective opening of safe harvest zones, increased harvest limits during low risk periods, and early harvest in anticipation of impending HAB events. The aims of this study are to show trends in nearshore domoic acid along the US west coast in recent years, including the recent establishment of a new seed bed of highly-toxic Pseudo-nitzschia, and to explore how early warning systems are a useful tool to mitigate the human and environmental health and economic impacts associated with harmful algal blooms.

Present-day ocean color satellite sensors, which principally provide reliable data on chlorophyll, sediments, and colored dissolved organic material in the open ocean, are not well suited for coastal and inland water studies for a variety of reasons, including coarse spatial and spectral resolution plus challenges with atmospheric correction. National Aeronautics and Space Administration (NASA) airborne mission concepts tested in 2011, 2013, 2017, and 2018 over Monterey Bay, CA, and nearby inland waters have demonstrated the feasibility of improving airborne monitoring and research activities in case-1 and case-2 aquatic ecosystems through the combined use of state-of-the-art above- and in-water measurement capabilities. These competencies have evolved through time to produce a sensor-web approach: imaging spectrometer, microradiometers, and a sun photometer (airborne) with their analogous algorithms, and with corresponding in-water radiometers and ground-based sun photometry. The NASA airborne instrument suite and mission concept demonstrations, leveraging high-quality above- and in-water data, significantly improves the fidelity as well as the spatial and spectral resolution of observations for studying and monitoring water quality in oceanic, coastal, and inland water ecosystems. The goal of this series of projects was to develop and fly a portable airborne sensor suite for NASA science missions focusing on a gradient of water types from oligotrophic to turbid waters addressing the challenges of an optically complex coastal ocean zone and inland waters. The airborne radiometry in this range of aquatic conditions and sites has supported improved results of studies of water quality and biogeochemistry and provides capabilities for research areas such as ocean productivity and biogeochemistry; aquatic impacts of coastal landscape alteration; coastal, estuarine, and inland waters ecosystem productivity; atmospheric correction; and regional climate variability.

The California Current System (CCS) is a highly productive region because of wind-driven upwelling, which supplies nutrients to the euphotic zone. Numerous studies of the relationship between phytoplankton productivity and wind patterns suggest that an intermediate wind speed yields the most productivity on the shelf. However, few studies have considered the productivity-wind relationship across the entire CCS, including the Northern CCS (north of 42°N), an unusually productive region with highly variable upwelling- and downwelling-favorable winds. Using satellite chlorophyll concentration from GlobColour together with QuikSCAT and ASCAT winds, we examine the relationship between shelf (shallower than the 150 m isobath) chlorophyll concentration and wind patterns in the Central and Northern CCS. Results from this empirical analysis suggest that while there is a dome-shaped relationship between mean chlorophyll concentration and wind stress for the whole system, the Central CCS and Northern CCS have significantly different relationships, which is evident in the separation between their mean chlorophyll concentration-wind stress curves. The Northern CCS also supports high chlorophyll concentration during downwelling-favorable winds. To understand this difference in chlorophyll concentration-wind stress relationships, results from particle tracking experiments using a ROMS model of the Northern CCS are used to map shelf retention times with respect to wind patterns. These results suggest that on the 1°-latitude scale, the effect of wind intermittency on retention is minimal in the Northern CCS; however, this result does not disqualify the influence of more complex controls on retention like wind intermittency on smaller spatial scales. Lastly, we present a revised hypothesis to describe the relationship between chlorophyll concentration and wind stress in the CCS that includes the influence of non-upwelling-derived nutrients in the Northern CCS.

The hardware and software capabilities of the compact-profiling hybrid instrumentation for radiometry and ecology (C-PHIRE) instruments on an unmanned surface vessel (USV) are evaluated. Both the radiometers and USV are commercial-off-the-shelf (COTS) products, with the latter being only minimally modified to deploy the C-PHIRE instruments. The hybridspectral C-PHIRE instruments consist of an array of 18 multispectral microradiometers with 10 nm wavebands spanning 320–875 nm plus a hyperspectral compact grating spectrometer (CGS) with 2048 pixels spanning 190–1000 nm. The C-PHIRE data were acquired and processed using two architecturally linked software packages, thereby allowing lessons learned in one to be applied to the other. Using standard data products and unbiased statistics, the C-PHIRE data were validated with those from the well-established compact-optical profiling system (C-OPS) and verified with the marine optical buoy (MOBY). Agreement between algorithm variables used to estimate colored dissolved organic matter (CDOM) absorption and chlorophyll a concentration were also validated. Developing and operating novel technologies, such as the C-PHIRE series of instruments, deployed on a USV increase the frequency and coverage of optical observations, which are required to fully support the present and next-generation validation exercises in radiometric remote sensing of aquatic ecosystems.

Understanding spatial variability of water quality in estuary systems is important for making monitoring decisions and designing sampling strategies. In San Francisco Bay, the largest estuary system on the west coast of North America, tracking the concentration of suspended materials in water is largely limited to point measurements with the assumption that each point is representative of its surrounding area. Strategies using remote sensing can expand monitoring efforts and provide a more complete view of spatial patterns and variability. In this study, we (1) quantify spatial variability in suspended particulate matter (SPM) concentrations at different spatial scales to contextualize current in-water point sampling and (2) demonstrate the potential of satellite and shipboard remote sensing to supplement current monitoring methods in San Francisco Bay. We collected radiometric data from the bow of a research vessel on three dates in 2019 corresponding to satellite overpasses by Sentinel-2, and used established algorithms to retrieve SPM concentrations. These more spatially comprehensive data identified features that are not picked up by current point sampling. This prompted us to examine how much variability exists at spatial scales between 20 m and 10 km in San Francisco Bay using 10 m resolution Sentinel-2 imagery. We found 23–80% variability in SPM at the 5 km scale (the scale at which point sampling occurs), demonstrating the risk in assuming limited point sampling is representative of a 5 km area. In addition, current monitoring takes place along a transect within the Bay’s main shipping channel, which we show underestimates the spatial variance of the full bay. Our results suggest that spatial structure and spatial variability in the Bay change seasonally based on freshwater inflow to the Bay, tidal state, and wind speed. We recommend monitoring programs take this into account when designing sampling strategies, and that end-users account for the inherent spatial uncertainty associated with the resolution at which data are collected. This analysis also highlights the applicability of remotely sensed data to augment traditional sampling strategies. In sum, this study presents ways to supplement water quality monitoring using remote sensing, and uses satellite imagery to make recommendations for future sampling strategies.

Development of global ocean observing capacity for the biological EOVs is on the cusp of a step-change. Current capacity to automate data collection and processing and to integrate the resulting data streams with complementary data, openly available as FAIR data, is certain to dramatically increase the amount and quality of information and knowledge available to scientists and decision makers into the future. There is little doubt that scientists will continue to expand their understanding of what lives in the ocean, where it lives and how it is changing. However, whether this expanding information stream will inform policy and management or be incorporated into indicators for national reporting is more uncertain. Coordinated data collection including open sharing of data will help produce the consistent evidence-based messages that are valued by managers. The GOOS Biology and Ecosystems Panel is working with other global initiatives to assist this coordination by defining and implementing Essential Ocean Variables. The biological EOVs have been defined, are being updated following community feedback, and their implementation is underway. In 2019, the coverage and precision of a global ocean observing system capable of addressing key questions for the next decade will be quantified, and its potential to support the goals of the UN Decade of Ocean Science for Sustainable Development identified. Developing a global ocean observing system for biology and ecosystems requires parallel efforts in improving evidence-based monitoring of progress against international agreements and the open data, reporting and governance structures that would facilitate the uptake of improved information by decision makers.

Harmful algal blooms (HABs) produce local impacts in nearly all freshwater and marine systems. They are a problem that occurs globally requiring an integrated and coordinated scientific understanding, leading to regional responses and solutions. Given that these natural phenomena will never be completely eliminated, an improved scientific understanding of HAB dynamics coupled with monitoring and ocean observations, facilitates new prediction and prevention strategies. Regional efforts are underway worldwide to create state-of-the-art HAB monitoring and forecasting tools, vulnerability assessments, and observing networks. In the United States, these include Alaska, Pacific Northwest, California, Gulf of Mexico, Gulf of Maine, Great Lakes, and the United States Caribbean islands. This paper examines several regional programs in the United States, European Union, and Asia and concludes that there is no one-size-fits-all approach. At the same time, successful programs require strong coordination with stakeholders and institutional sustainability to maintain and reinforce them with new automating technologies, wherever possible, ensuring integration of modeling efforts with multiple regional to national programs. Recommendations for scaling up to a global observing system for HABs can be summarized as follows: (1) advance and improve cost-effective and sustainable HAB forecast systems that address the HAB-risk warning requirements of key end-users at global and regional levels; (2) design programs that leverage and expand regional HAB observing systems to evaluate emerging technologies for Essential Ocean Variables (EOVs) and Essential Biodiversity Variables (EBVs) in order to support interregional technology comparisons and regional networks of observing capabilities; (3) fill the essential need for sustained, preferably automated, near real-time information from nearshore and offshore sites situated in HAB transport pathways to provide improved, advanced HAB warnings; (4) merge ecological knowledge and models with existing Earth System Modeling Frameworks to enhance end-to-end capabilities in forecasting and scenario-building; (5) provide seasonal to decadal forecasts to allow governments to plan, adapt to a changing marine environment, and ensure coastal industries are supported and sustained in the years ahead; and (6) support implementation of the recent calls for action by the United Nations Decade 2010 Sustainable Development Goals (SDGs) to develop indicators that are relevant to an effective and global HAB early warning system.

A Correction to this paper has been published: https://doi.org/10.1038/s42003-021-01993-7

Developing enduring capacity to monitor ocean life requires investing in people and their institutions to build infrastructure, ownership, and long-term support networks. International initiatives can enhance access to scientific data, tools and methodologies, and develop local expertise to use them, but without ongoing engagement may fail to have lasting benefit. Linking capacity development and technology transfer to sustained ocean monitoring is a win-win proposition. Trained local experts will benefit from joining global communities of experts who are building the comprehensive Global Ocean Observing System (GOOS). This two-way exchange will benefit scientists and policy makers in developing and developed countries. The first step toward the GOOS is complete: identification of an initial set of biological Essential Ocean Variables (EOVs) that incorporate the Group on Earth Observations (GEO) Essential Biological Variables (EBVs), and link to the physical and biogeochemical EOVs. EOVs provide a globally consistent approach to monitoring where the costs of monitoring oceans can be shared and where capacity and expertise can be transferred globally. Integrating monitoring with existing international reporting and policy development connects ocean observations with agreements underlying many countries’ commitments and obligations, including under SDG 14, thus catalyzing progress toward sustained use of the ocean. Combining scientific expertise with international capacity development initiatives can help meet the need of developing countries to engage in the agreed United Nations (UN) initiatives including new negotiations for the conservation and sustainable use of marine biological diversity of areas beyond national jurisdiction, and the needs of the global community to understand how the ocean is changing.

Measurements of the status and trends of key indicators for the ocean and marine life are required to inform policy and management in the context of growing human uses of marine resources, coastal development, and climate change. Two synergistic efforts identify specific priority variables for monitoring: Essential Ocean Variables (EOVs) through the Global Ocean Observing System (GOOS), and Essential Biodiversity Variables (EBVs) from the Group on Earth Observations Biodiversity Observation Network (GEO BON) (see Data Sheet 1 in Supplementary Materials for a glossary of acronyms). Both systems support reporting against internationally agreed conventions and treaties. GOOS, established under the auspices of the Intergovernmental Oceanographic Commission (IOC), plays a leading role in coordinating global monitoring of the ocean and in the definition of EOVs. GEO BON is a global biodiversity observation network that coordinates observations to enhance management of the world's biodiversity and promote both the awareness and accounting of ecosystem services. Convergence and agreement between these two efforts are required to streamline existing and new marine observation programs to advance scientific knowledge effectively and to support the sustainable use and management of ocean spaces and resources. In this context, the Marine Biodiversity Observation Network (MBON), a thematic component of GEO BON, is collaborating with GOOS, the Ocean Biogeographic Information System (OBIS), and the Integrated Marine Biosphere Research (IMBeR) project to ensure that EBVs and EOVs are complementary, representing alternative uses of a common set of scientific measurements. This work is informed by the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM), an intergovernmental body of technical experts that helps international coordination on best practices for observing, data management and services, combined with capacity development expertise. Characterizing biodiversity and understanding its drivers will require incorporation of observations from traditional and molecular taxonomy, animal tagging and tracking efforts, ocean biogeochemistry, and ocean observatory initiatives including the deep ocean and seafloor. The partnership between large-scale ocean observing and product distribution initiatives (MBON, OBIS, JCOMM, and GOOS) is an expedited, effective way to support international policy-level assessments (e.g., the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services or IPBES), along with the implementation of international development goals (e.g., the United Nations Sustainable Development Goals).

Retrievals of ocean surface chlorophyll-a concentration (Chla) by multiple ocean color satellite sensors (SeaWiFS, MODIS-Terra, MODIS-Aqua, MERIS, VIIRS) using standard algorithms were evaluated in the California Current using a large archive of in situ measurements. Over the full range of in situ Chla, all sensors produced a coefficient of determination (R2) between 0.79 and 0.88 and a median absolute percent error (MdAPE) between 21% and 27%. However, at in situ Chla > 1 mg m−3, only products from MERIS (both the ESA produced algal_1 and NASA produced chlor_a) maintained reasonable accuracy (R2 from 0.74 to 0.52 and MdAPE from 23% to 31%, respectively), while the other sensors had R2 below 0.5 and MdAPE higher than 36%. We show that the low accuracy at medium and high Chla is caused by the poor retrieval of remote sensing reflectance.

As a demonstrator for technologies for the next generation of ocean color sensors, the Hyperspectral Imager for the Coastal Ocean (HICO) provides enhanced spatial and spectral resolution that is required to understand optically complex aquatic environments. In this study we apply HICO, along with satellite remote sensing and in situ observations, to studies of phytoplankton ecology in a dynamic coastal upwelling environment—Monterey Bay, CA, USA. From a spring 2011 study, we examine HICO-detected spatial patterns in phytoplankton optical properties along an environmental gradient defined by upwelling flow patterns and along a temporal gradient of upwelling intensification. From a fall 2011 study, we use HICO’s enhanced spatial and spectral resolution to distinguish a small-scale “red tide” bloom, and we examine bloom expansion and its supporting processes using other remote sensing and in situ data. From a spectacular HICO image of the Monterey Bay region acquired during fall of 2012, we present a suite of algorithm results for characterization of phytoplankton, and we examine the strengths, limitations, and distinctions of each algorithm in the context of the enhanced spatial and spectral resolution.

Presently, operational ocean color satellite sensors are designed with a legacy perspective for sampling the open ocean primarily in the visible domain, while high spatial resolution sensors such as Sentinel-2, Sentinel-3, and Landsat8 are increasingly used for observations of coastal and inland water quality. Next-generation satellites such as the NASA Plankton, Aerosol, Cloud and ocean Ecosystem (PACE) and Surface Biology and Geology (SBG) sensors are anticipated to increase spatial and/or spectral resolution. An important consideration is determining the minimum signal-to-noise ratio (SNR) needed to retrieve typical biogeochemical products, such as biomass, in aquatic systems, and whether legacy sensors can be used for algorithm development. Here, we evaluate SNR and remote-sensing reflectance (Rrs) uncertainty for representative bright and dim targets in coastal California, USA. The majority of existing sensors fail to meet proposed criteria. Despite these limitations, uncertainties in retrieved biomass as chlorophyll or normalized difference vegetation index (NDVI) remain well below a proposed threshold of 17.5%, suggesting that existing sensors can be used in coastal systems. Existing commercially available in-water and airborne instrument suites can exceed all proposed thresholds for SNR and Rrs uncertainty, providing a path forward for collection of calibration and validation data for future satellite missions.

Satellite estimation of oceanic chlorophyll-a content has enabled characterization of global phytoplankton stocks, but the quality of retrieval for many ocean color products (including chlorophyll-a) degrades with increasing phytoplankton biomass in eutrophic waters. Quality control of ocean color products is achieved primarily through the application of masks based on standard thresholds designed to identify suspect or low-quality retrievals. This study compares the masked and unmasked fractions of ocean color datasets from two Eastern Boundary Current upwelling ecosystems (the California and Benguela Current Systems) using satellite proxies for phytoplankton biomass that are applicable to satellite imagery without correction for atmospheric aerosols. Evaluation of the differences between the masked and unmasked fractions indicates that high biomass observations are preferentially masked in National Aeronautics and Space Administration (NASA) ocean color datasets as a result of decreased retrieval quality for waters with high concentrations of phytoplankton. This study tests whether dataset modification persists into the default composite data tier commonly disseminated to science end users. Further, this study suggests that statistics describing a dataset’s masked fraction can be helpful in assessing the quality of a composite dataset and in determining the extent to which retrieval quality is linked to biological processes in a given study region.

Studies of phytoplankton ecology in Monterey Bay, CA, USA, using the Hyperspectral Imager for the Coastal Ocean (HICO) and other satellite remote sensing and in-situ observations, were presented in [1]. [...]

A two and a half year old spayed female Miniature Australian Shepherd presented to a Montana veterinary clinic with acute onset of anorexia, vomiting and depression. Two days prior, the dog was exposed to an algal bloom in a community lake. Within h, the animal became lethargic and anorexic, and progressed to severe depression and vomiting. A complete blood count and serum chemistry panel suggested acute hepatitis, and a severe coagulopathy was noted clinically. Feces from the affected dog were positive for the cyanobacterial biotoxin, microcystin-LA (217 ppb). The dog was hospitalized for eight days. Supportive therapy consisted of fluids, mucosal protectants, vitamins, antibiotics, and nutritional supplements. On day five of hospitalization, a bile acid sequestrant, cholestyramine, was administered orally. Rapid clinical improvement was noted within 48 h of initiating oral cholestyramine therapy. At 17 days post-exposure the dog was clinically normal, and remained clinically normal at re-check, one year post-exposure. To our knowledge, this is the first report of successful treatment of canine cyanobacterial (microcystin) toxicosis. Untreated microcystin intoxication is commonly fatal, and can result in significant liver damage in surviving animals. The clinical success of this case suggests that oral administration of cholestyramine, in combination with supportive therapy, could significantly reduce hospitalization time, cost-of-care and mortality for microcystin-poisoned animals

Pseudo-nitzschia blooms often occur in coastal and open ocean environments, sometimes leading to the production of the neurotoxin domoic acid that can cause severe negative impacts to higher trophic levels. Increasing evidence suggests a close relationship between phytoplankton bloom and bacterial assemblages, however, the microbial composition and succession during a bloom process is unknown. Here, we investigate the bacterial assemblages before, during and after toxic and non-toxic Pseudo-nitzschia blooms to determine the patterns of bacterial succession in a natural bloom setting. Opportunistic sampling of bacterial community profiles were determined weekly at Santa Cruz Municipal Wharf by 454 pyrosequencing and analyzed together with domoic acid levels, phytoplankton community and biomass, nutrients and temperature. We asked if the bacterial communities are similar between bloom and non-bloom events and if domoic acid or the presence of toxic algal species acts as a driving force that can significantly structure phytoplankton-associated bacterial communities. We found that bacterial diversity generally increases when Pseudo-nitzschia numbers decline. Furthermore, bacterial diversity is higher when the low-DA producing P. fraudulenta dominates the algal bloom while bacterial diversity is lower when high-DA producing P. australis dominates the algal bloom, suggesting that the presence of algal toxin can structure bacterial community. We also found bloom-related succession patterns among associated bacterial groups; Gamma-proteobacteria, were dominant during low toxic P. fraudulenta blooms comprising mostly of Vibrio spp., which increased in relative abundance (6%-65%) as the bloom progresses. On the other hand, Firmicutes bacteria comprising mostly of Planococcus spp. (12%- 86%) dominate during high toxic P. australis blooms, with the bacterial assemblage showing the same bloom-related successional patterns in 3 independent bloom events. Other environmental variables such as nitrate and phosphate and temperature appear to influence some low abundant bacterial groups as well. Our results suggest that phytoplankton-associated bacterial communities are strongly affected not just by phytoplankton bloom in general, but also by the type of algal species that dominates in the natural bloom.

The U.S. Environmental Protection Agency banned the use of polychlorinated biphenyls (PCBs) in 1979, due to the high environmental and public health risks with which they are associated. However, PCBs continue to persist in the San Francisco Bay (SFB), often at concentrations deemed unsafe for humans. In situ PCB monitoring within the SFB is extremely limited, due in large part to the high monetary costs associated with sampling. Here we offer a cost effective alternative to in situ PCB monitoring by demonstrating the feasibility of indirectly quantifying PCBs in the SFB via satellite remote sensing using a two-step approach. First, we determined the relationship between in situ PCB concentrations and suspended sediment concentrations (SSC) in the SFB. We then correlated in situ SSC with spatially and temporally consistent Landsat 8 and Sentinel 2A reflectances. We demonstrate strong relationships between SSC and PCBs in all three SFB sub-embayments (R2 > 0.28–0.80, p < 0.01), as well as a robust relationship between SSC and satellite measurements for both Landsat 8 and Sentinel 2A (R2 > 0.72, p < 0.01). These relationships held regardless of the atmospheric correction regime that we applied. The end product of these relationships is an empirical two-step relationship capable of deriving PCBs from satellite imagery. Our approach of estimating PCBs in the SFB by remotely sensing SSC is extremely cost-effective when compared to traditional in situ techniques. Moreover, it can also be utilized to generate PCB concentration maps for the SFB. These maps could one day serve as an important tool for PCB remediation in the SFB, as they can provide valuable insight into the spatial distribution of PCBs throughout the bay, as well as how this distribution changes over time.

Toxin producing cyanobacterial blooms have increased globally in recent decades in both frequency and intensity. Despite the recognition of this growing risk, the extent and magnitude of cyanobacterial blooms and cyanotoxin prevalence is poorly characterized in the heavily populated region of southern California. Recent assessments of lentic waterbodies (depressional wetlands, lakes, reservoirs and coastal lagoons) determined the prevalence of microcystins and, in some cases, additional cyanotoxins. Microcystins were present in all waterbody types surveyed although toxin concentrations were generally low across most habitats, as only a small number of sites exceeded California’s recreational health thresholds for acute toxicity. Results from passive samplers (Solid Phase Adsorption Toxin Tracking (SPATT)) indicated microcystins were prevalent throughout lentic waterbodies and that traditional discrete samples underestimated the presence of microcystins. Multiple cyanotoxins were detected simultaneously in some systems, indicating multiple stressors, the risk of which is uncertain since health thresholds are based on exposures to single toxins. Anatoxin-a was detected for the first time from lakes in southern California. The persistence of detectable microcystins across years and seasons indicates a low-level, chronic risk through both direct and indirect exposure. The influence of toxic cyanobacterial blooms is a more complex stressor than presently recognized and should be included in water quality monitoring programs.